Aparna Balagopalan is a third year PhD student in EECS at MIT. Her research broadly focuses on developing fair and robust models by re-evaluating and surfacing assumptions in machine learning-based measurements in socially-relevant contexts like healthcare. Prior to this, she received a Master’s degree from the University of Toronto and a BTech degree from IIT Guwahati. She currently holds an Amazon Doctoral Fellowship from MIT’s Science Hub.
I am studying the generalisability of machine learning models applied to healthcare. The dynamic and adaptive nature of healthcare is reflected in the data that is collected in electronic health records. Sometimes we can anticipate these changes, and other times we need the model to be robust to these changes so that their decisions are reliable. In order to integrate machine learning into clinical models, we must understand when it fails, where it fails, and whom it fails to serve.